Preoperative diagnosis of cavernous hemangioma presenting with melena using wireless capsule endoscopy of the small intestine.
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ABSTRACT:
SUBMITTER: Akazawa Y
PROVIDER: S-EPMC4798841 | biostudies-other | 2016 Mar
REPOSITORIES: biostudies-other
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Project description:Gastrointestinal metastases of lung cancer are relatively uncommon, yet occur at a higher frequency than would be expected among patients that exhibit a longer survival interval. Metastases that arise in the small intestines are often associated with no or few symptoms such that their early diagnosis can be challenging. In this report, we describe an extremely rare case of a lung squamous cell carcinoma that had metastasized to the small intestine and was associated with symptoms of abdominal pain. The patient underwent capsule endoscopy which detected an irregular mass in the distal ileum that was hemorrhagic, after which laparoscopic ileal resection and anastomosis in parallel with partial bladder resection were performed. Subsequent pathological biopsy confirmed that the intestinal mass was consistent with metastatic squamous cell carcinoma. With surgery and subsequent maintenance therapy with targeted drugs, the survival of the patient was more than 6 months. As a noninvasive testing strategy, capsule endoscopy can be easily performed to support etiological diagnostic efforts in cases where other diagnostic options are lacking. Early diagnosis and therapeutic intervention can contribute to better prognostic outcomes for GMLC patients.
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Project description:BackgroundWireless capsule endoscopy (WCE) is considered to be a powerful instrument for the diagnosis of intestine diseases. Convolution neural network (CNN) is a type of artificial intelligence that has the potential to assist the detection of WCE images. We aimed to perform a systematic review of the current research progress to the CNN application in WCE.MethodsA search in PubMed, SinoMed, and Web of Science was conducted to collect all original publications about CNN implementation in WCE. Assessment of the risk of bias was performed by Quality Assessment of Diagnostic Accuracy Studies-2 risk list. Pooled sensitivity and specificity were calculated by an exact binominal rendition of the bivariate mixed-effects regression model. I2 was used for the evaluation of heterogeneity.Results16 articles with 23 independent studies were included. CNN application to WCE was divided into detection on erosion/ulcer, gastrointestinal bleeding (GI bleeding), and polyps/cancer. The pooled sensitivity of CNN for erosion/ulcer is 0.96 [95% CI 0.91, 0.98], for GI bleeding is 0.97 (95% CI 0.93-0.99), and for polyps/cancer is 0.97 (95% CI 0.82-0.99). The corresponding specificity of CNN for erosion/ulcer is 0.97 (95% CI 0.93-0.99), for GI bleeding is 1.00 (95% CI 0.99-1.00), and for polyps/cancer is 0.98 (95% CI 0.92-0.99).ConclusionBased on our meta-analysis, CNN-dependent diagnosis of erosion/ulcer, GI bleeding, and polyps/cancer approached a high-level performance because of its high sensitivity and specificity. Therefore, future perspective, CNN has the potential to become an important assistant for the diagnosis of WCE.
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Project description:IntroductionSpinal hemangiomas are benign vascular tumors that most commonly originate from the osseous structures of the spinal column. Epidural spinal hemangiomas without osseous involvement are uncommon and are classified as pure epidural spinal hemangiomas. Extraosseous spinal epidural cavernous hemangiomas are rarely described and among available reports; most patients present with slowly progressive neurological symptoms. Herein, we present a novel case of acute neurological dysfunction from a pure spinal epidural hemangioma that was managed through surgical resection with good neurological recovery at follow-up.Case presentationA 45-year-old previously healthy man presented to the emergency room with sudden inability to ambulate and was found to have bilateral lower extremity weakness. Magnetic resonance imaging of the spine demonstrated an epidural mass extending out of the right T5/6 neural foramen. The mass enhanced heterogeneously, and the preoperative diagnosis favored an atypical schwannoma. The lesion was surgically removed en-bloc through a midline posterior decompression with instrumentation. Histopathologic examination confirmed cavernous hemangioma pathology. Within 6 weeks of the surgical intervention, the patient had regained full sensorimotor function and these effects were durable through long term follow-up.DiscussionPure spinal epidural hemangiomas are rare and generally have an insidious clinical course. This case report highlights that these uncommon lesions may present with substantial and acute neurological dysfunction requiring urgent neurosurgical intervention. This should prompt clinicians to consider cavernous hemangioma in the differential diagnosis of patients presenting with acute neurological deterioration and an epidural spinal tumor.
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Project description:Benign cardiac hemangiomas are rare tumors that may present in or out side of the heart, epicardium being the most common site. Echocardiography is the method of choice in diagnosing cardiac masses and though 3D TEE may seem to add exact information about the location, the time constraint in doing a comprehensive examination along with 3D rendering inside operation room may become an hindrance.
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Project description:BackgroundInterpretation of capsule endoscopy images or movies is operator-dependent and time-consuming. As a result, computer-aided diagnosis (CAD) has been applied to enhance the efficacy and accuracy of the review process. Two previous meta-analyses reported the diagnostic performance of CAD models for gastrointestinal ulcers or hemorrhage in capsule endoscopy. However, insufficient systematic reviews have been conducted, which cannot determine the real diagnostic validity of CAD models.ObjectiveTo evaluate the diagnostic test accuracy of CAD models for gastrointestinal ulcers or hemorrhage using wireless capsule endoscopic images.MethodsWe conducted core databases searching for studies based on CAD models for the diagnosis of ulcers or hemorrhage using capsule endoscopy and presenting data on diagnostic performance. Systematic review and diagnostic test accuracy meta-analysis were performed.ResultsOverall, 39 studies were included. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of ulcers (or erosions) were .97 (95% confidence interval, .95-.98), .93 (.89-.95), .92 (.89-.94), and 138 (79-243), respectively. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of hemorrhage (or angioectasia) were .99 (.98-.99), .96 (.94-0.97), .97 (.95-.99), and 888 (343-2303), respectively. Subgroup analyses showed robust results. Meta-regression showed that published year, number of training images, and target disease (ulcers vs erosions, hemorrhage vs angioectasia) was found to be the source of heterogeneity. No publication bias was detected.ConclusionsCAD models showed high performance for the optical diagnosis of gastrointestinal ulcer and hemorrhage in wireless capsule endoscopy.
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